The present invention relates to the field of information systems for the use in reimbursement of medical provider billing, such as anesthesia billing, in regards to the detection, analysis and prevention of overbilling or fraud. It also allows for the development of profiles and utilizes a database relating to specific providers of medical care, such as anesthesiologists.
Healthcare costs in the United States continue to rise because of a growing aging population, better education, new drugs and technology and greater healthcare benefits from the government as well as the insurance industry. Healthcare costs are over one trillion dollars a year with fraud and abuse representing about 10% to 15% of this. Conservative estimates put the cost of fraud to the country at over 100 billion dollars a year. The industry, as well as the government, recognizes this problem and have allocated manpower through the FBI and Department of Justice to crack down using the False Claims Act to prosecute these violators. But the discovery of the fraud is still a weak component both with the government as well as on the insurance industry""s side.
At present, the federal government relies on personal informants, such as whistle blowers, for discovery, while the insurance industry relies on special investigation units, which are understaffed, lack the proper medical and accounting background and do not have the proper resources to discover where the false claims lie. In addition, the claims process is performed by employees called coders. They have no medical background, let alone have any exposure to medically arcane information such as anesthesia nomenclature. No one in the process of evaluating a claim submitted knows, for example, how to read an anesthesia chart. But the anesthesia chart is a blueprint for whatever billing is submitted by the anesthesiologist.
The head of fraud at insurance companies usually has a background in police work and because of limited medical knowledge, can neither decipher nor interpret technical medical practice information such as an anesthesia chart. Only the medical director of anesthesia, for example, can properly interpret and analyze an anesthesiologist""s claim for payment but such proper and qualified anesthesiologist claim interpretations and analysis occurs currently in only 0.01% of anesthesiologist payment claims submitted.
Because of diminished reimbursements throughout the medical community, some doctor providers submit exaggerated billing claims so as to keep their revenue from declining. The software of the present invention is probative of fraud and is not merely an indicator of fraud. The software of the present invention uses a database comprising a history of over a million anesthesia claims to determine whether a particular claim being screened may be aberrant and therefore potentially fraudulent. Thereafter, the doctor in question who submitted the screened claim in question is profiled statistically to see how many standard deviations he or she is deviant generally in submitting claims as compared to his or her peers in regard to his or her pattern of claim billing. No other software process for detecting medical fraud has a built in database nor is any other software capable of addressing specific areas of specialty medical practice, which has triggers which are functionally data processing filters that operate as fraud flags built in to designate and recognize fraudulent bills submitted by medical providers, such as anesthesiologists.
Fraud detection and investigation with the utilization of the unique software of the present invention enables one to identify rapidly and accurately the abuse patterns specific to areas of medical specialty practice provider billing, such as anesthesia billing practices.
Once the software has identified abuse, the present invention commences a drill down process. Anomalous claims that are fraud-suspect are investigated and patterns of fraudulent billing from individual medical care providers are substantiated. This drill-down process, for anesthesisology, for example, utilizes more than sixty years of combined experience of anesthesiologists who detect what appears to the non-anesthesiologist to be subtle abuses but which nonetheless constitute patterns and practices of fraud and abuse in medical billing.
After identifying fraud-suspect aberrations of submitted claims, a proven state of the art recover process takes place using professional staff. This unique recovery process includes a medical provider, such as an anesthesiologist, addressing specific billing issues with the anesthesia provider who submitted fraud-suspect bills. Therefore, the present invention eliminates the arcane nomenclature, confusion and the involvement of three or four layers of non-knowledgeable insurance personnel who lack the requisite skill to analyze even rudimentary medical records, let alone such sophisticated and thus obfuscated and arcane material as anesthesia records.
Among related patents which describe attempts to monitor medical provider billing while preventing fraudulent billing include U.S. Pat. No. 5,995,937 of DeBusk.
DeBusk ""937 describes a method of structuring software for creating a health care information management system. In contrast to DeBusk ""937, in the present invention the use of software and expert consultants is used to screen health care billing claims to flag possible fraud for further investigation.
However, DeBusk ""937 uses the notions of NODE, MODULE, CONTAINER, RESOURCE AND DATA to describe its software system. In FIG. 2 it uses a xe2x80x9cclinical pathwayxe2x80x9d example which shows how an anesthesiologist fits in. DeBusk""s examples of fraud relate more to inventory control of supplies in hospitals than the data processing comparison of hospital records with physician payment claim records to flag inconsistencies where there should not be any, which is one of the linchpins of the present invention. The last paragraph of DeBusk ""937 claim 6 which states xe2x80x9canalyzing the utilization study module . . . xe2x80x9d relates to detecting trends in health care data.
U.S. Pat. No. 6,070,141 of Houvener basically deals with assessing the quality of an identification transaction in an effort to limit identity-based fraud during on-line transactions, which is vastly different from the present invention. It does create a database of xe2x80x9cquality score assignmentsxe2x80x9d that are distinguished from the data processing fraud flag filters that are the triggers of the present invention. Houvener ""141 uses quality indicators to determine the level of scrutiny. It adjusts historical data as a function of transaction data, which is also used in many commercial applications and is closely related to surveys and polls.
U.S. Pat. No. 5,991,758 of Ellard involves a system and method for indexing information about entities from different information sources. In this way, an entity may be related to records in one or more databases. While the abstract objective of Ellard ""758 bears some relation to comparing hospital billing records to those of a physician, the methods used are different from those of the present invention. Ellard ""758 uses the notion of a master entity index, MEI. Ellard ""758 uses the addition of confidence levels for matching attributes to compare to a threshold level for selecting data records for display, which may be construed as data processing filter triggers.
Moreover, U.S. Pat. No. 6,058,380 of Anderson describes a system for processing financial invoices for billing errors. Anderson ""380 describes in Table 3 therein the use of xe2x80x9creasonabilityxe2x80x9d criteria and historical data to determine if billing errors have occurred.
Additionally, the New York Post, Jul. 16, 2000 edition, reports as its leading article on page 1 an article entitled xe2x80x9cRent-A-Doc: MD""s lease their names to front for medical millsxe2x80x9d about medical providers using a multiplicity of entities with different addresses to boost billing.
Currently, these major problems exist because the insurance industry separates their claims departments for handling hospital claims from the physician claims, so that they are unable to discover the situations disclosed in the New York Post article.
Therefore an object of the present invention is to provide a system which monitors medical provider billing to prevent fraud.
An applications object of the present invention is to selectively manage a user defined, user configurable database that is provided from standardized resources. In contrast to the present invention, at the current time, upon receipt of a claim by the payer, there is little to guide the claim processor in order to identify a claim being one that should be paid or one that should be investigated. Therefore, an object of the present invention is to institute several triggers, which are data processing filters capable of flagging fraud-suspect data in a medical provider claim for payment. The triggers interface with the information provided in the claim itself.
In addition, the present invention recognizes that there is a need to stop improper provider billing in medicine, in regard to preventing overpayments that are normally processed by the payers. The system of the present invention processes the information at a rate that allows the payer to effectively keep up its commitments while assuring that overpayments no longer occur.
At the present time, medical providers submit claims separately from the medical institutions, such as hospitals. The providers file claims for payment on a standardized 92UB1450 form whereas the hospitals use the standardized HCFA 1500 form. These two forms are submitted either by electronic or paper filing to respective claims departments of the insurance carrier payers. However, neither these two forms nor the data they contain even interface with each other, nor are their combined data evaluated side by side by the same insurance company coder to see if there are any inconsistencies.
Therefore it is also an object of the present invention to provide a proprietary fraud-preventive system of analysis of medical provider payment claims which allows the claim processor to take the data from the pertinent fields from each respective claim form and compare them for any discrepancies beyond allowable circumstances.
By comparing the fields, such as #24D or 24G in the HCFA 1500 form with the fields such as #710 and #370 respectively in the 92UB1450 forms, the present invention probatively determines if overbilling and/or patterns of fraud have occurred.
With the data provided by these claims, it is also an object of the present invention to be able to generate specific profiles pertaining to an individual provider""s billing habits. This enables the insurance company payers to be able to identify those providers that have submitted false claims, which, hence, drive up the cost of health care for the country.
The present invention has an advantage of not being biased, because it utilizes a huge historical reference database of previous claims to ensure accuracy and validation of data processing using the fraud filters of this invention. In addition, in the specialty medical field of anesthesia billing is performed as a taxi cab driver bills his fare, i.e., there is an initial charge and then the calculation of time per unit. The software of the present invention and overall solutions hold the biller accountable to a reasonable time frame by constructing the following preventive claims processing structure.
It is also yet another object of the present invention to improve over the disadvantages of the prior art.
The present invention is a health care fraud-detection information management system that uses a pre-existing database of medical specialty claims, such as anesthesia claims, to profile the billing behavior of medical specialist providers, such as anesthesiologists. The software helps the user to determine which of the claims submitted by the providers are within accepted guidelines and industry standards. The information management system allows for the creation by the user of software objects representative of specific events and/or resources, which occur during health care rendition, such as the administration of anesthesia to the patient.
For example, presently, anesthesia claims are processed by insurance carrier coders who have no medical knowledge foundation to interpret these claims. In contrast, the software of the present invention relies on data processing filters developed with anesthesiologist skill and therefore, since the filters xe2x80x9cknow what to look forxe2x80x9d identifies providers who have submitted improper false claims. This is accomplished by the software that compares a submitted claim with the reference database of the present invention as well as the reference data accumulated data over time supplied by sources originating from hospitals, physicians and professional societies. Unlike any other software, the present system is probative for each and every screened claim. The analysis provided by the present invention is thus more than a mere indicator that functions by comparing billing practices on the basis of differences quantified by statistical standard deviations.
At the core of the application of the present invention are nine unique triggers that respectively comprise data processing filters for flagging fraud-suspect data within claims submitted for payment by health care providers. The triggers, or data processing filters, are described below. The software application was created using spreadsheet software, such as that developed by Hyperion, Inc. and known as Essbase software.
The information management system includes:
1. a computer system
2. a display
3. a storage
4. a processor
5. an input means
6. operating and analytical software
7. a database of historically relevant comparative data
Specifically, the software of the present invention utilizes triggers which highlight those claims that indicate possible fraudulent submission.
In contrast to the presently existing accounting systems, the system of the present invention combines the claims off of the 92UB1450 form submitted by the hospital, with the HCFA 1500 form submitted by the health care (e.g., doctor, such as an anesthesiologist). The code fields in question that are examined are 24D on the HCFA form if the claim was submitted to an insurance company or field number 24G if the claim was for a federally funded Medicare patient. These fields are compared to fields 710 and 370 -on the hospitals insurance claims form. At times, these fields are not complete, therefore, part of the system includes requiring any claim submission by the hospital to have time units recorded in field 710 or field 370 in column 42 (REV CO.) of the 92UB1450 form. These time units are recorded by either the recovery room nurse pertaining to field 710, or by the operating room nurse pertaining to code number 370. If either of these times have fifteen minute""s difference between them and the provider""s times, such as the anesthesiologist times, then the claim will be labeled suspicious and a drill down process occurs using the physician""s other prior claims. The system then determines if this is a pattern of behavior on the part of the individual provider for improperly reporting time, or whether this was the rare case that the patient needed to have extra time for the anesthesiologist to tend to his well being.
This time comparison procedure adds full accountability to the anesthesiologists"" claim that the procedure, which was billed, was accurate. If not for the process and software of the present invention, a provider such as the anesthesiologist can submit fabricated and inflated times, thereby raising the rates in his bill to the insurance company.
In addition to comparing the anesthesiologists"" HCFA 1500 form to the hospitals"" 92UB1450 submission, the system of the present invention compares the surgeons"" HCFA 1500 form submitted for the same patient. By comparing data from the surgeon""s HCFA 1500 with data from the same form submitted by an anesthesiologist, the system identifies and thus deters a process of fraudulent upcoding. Upcoding is a way for an anesthesiologist or other health care provider to fraudulently fabricate an inflated payment claim in a manner presently very difficult to detect by ascribing a higher time unit value to a case than that which the surgeon gives for the same patient in the same surgical operation at the same time and place. The fraud detection method of the present invention compares, for example, the anesthesiologist claimed codes listed in field #21 on the HCFA form with those claimed by the surgeon for the same surgical operation on the same patient at the same time and place.
Anesthesia is a unique specialty in that it is the only specialty in medicine that is reimbursed by time units. Up until now, neither the insurance industry, the government, hospital nor the patient themselves, had any idea if the time units that were submitted were accurate. Now, by using the software of the present invention in conjunction with its preventive business model for stopping fraud, a compliance committee, an insurance company and the government, can get an accurate account for an anesthesiologists, claim. The system develops a profile of a provider""s billing behavior and compares it to his peers. In addition, the software is probative because it has a set value to each and every time submitted.
The software uses triggers to alert the insurance carrier if the provider""s billing falls outside of a predetermined norm. While other data processing filter triggers may be used to flag fraud-suspect data, the following triggers, or data processing filters that generate fraud flags, are illustrative.
Time Differences:
Anesthesiologists bill by unit value concerning the surgical procedure plus the time units. Standard time units are broken up into 15-minute intervals. Therefore, every 15 minutes that the anesthesiologist works is equal to one unit in value. The software fraud detection system of the present invention holds the anesthesiologist accountable by comparing his or her claim to the submission of times listed on the 92UB1450 form listed in field #370 and #710. These can be found under #42 REV CO. for the hospital billing form. Fields 24D and 24G of the HCFA 1500 form submitted by the anesthesiologists, for example, are compared. Any difference in times greater than a pre-selected amount results in the software generating a fraud flag for scrutiny and examination of a possibly fraudulent payment claim.
This can be stated as follows:
A=Start time (Anesthesiologist)xe2x88x92Start time (Hospital=# minutes 
B=End time (Anesthesiologist)xe2x88x92End time (Hospital)=# minutes 
Total Minutes=A+B 
Each 15-minute interval is then converted into 1 unit and billed as a unit. Times recorded by the hospital are start time that is when the patient comes into the operating room and end time when the anesthesiologist leaves the patient""s side in the recovery room. Deviation values are then calculated based on the deviation table below:
a.  greater than 20 minutesxe2x88x921 standard deviation
b.  greater than 45 minutesxe2x88x922 standard deviations
C.  greater than 50 minutesxe2x88x923 standard deviations
d.  greater than 65 minutesxe2x88x924 standard deviations
By holding the anesthesiologist accountable for his or her submission of times, the insurance industry prevents creation of time and false claims are recognized.
In addition, the software of the present invention has an existing database which compares the time units billed by the provider, such as an anesthesiologist, to the same procedure billed by many other similar providers, such as anesthesiologists.
Multiple Identifiers for Participators:
Within all insurance companies as well as Medicare, some physicians are participators and some are non-participators. The participators sign a contract to bill the particular payer at a set and reduced rate. Often a physician although contractually obligated to bill the reduced participator rate will bill the increased rate of a non-participator. The software of the present invention identifies these abusers by cross-referencing Tax I.D. numbers, different addresses used by participators, Medicare numbers and identifying at which hospital they performed the procedure. Most teaching hospitals have contractual obligations with Insurance Companies and doctors there typically are participators. As participators bound by contracts, doctors should not be able to attempt to fraudulently collect inflated payments for which they are ineligible by billing a non-participator (i.e., higher) rate. In some instances, some physicians can have more than one job or address and manipulate the system by also using another Tax I.D. or, billing in the name of another corporation. All of these abuses are exposed by the software of the present invention by comparing the health care providers non-varying identifying information, such as a Medicare number, with the name and address of a health care provider on a claim submitted for payment. Such a comparison will expose, for example, a particular anesthesiologist who bills a paying insurance carrier under multiple entity names and thereby confuses and obfuscates his/her real identity as presented to the payer, and at the same time obfuscates his/her true identity to the payer with the present result that payers are helpless to determine which individual medical care providers are improperly and fraudulently billing multiple rates for the same procedure by using multiple identities and thus purporting to be more than one provider for the simple reason that they presently know they can""t get caught.
Unbundling:
A common avenue for fraudulent bill inflation is for a doctor to unbundle his/her billing. Unbundling is the practice of taking one event of medical care rendition or one surgical procedure, for example, that should be billed under one code and billing a number of codes derived from that one procedure. For example, if a woman has an epidural for labor pain, but must deliver the baby by cesarean section, an anesthesiologist who unbundles his/her billing may bill individual unbundled codes for:
1. Labor Pain
2. Cesarean Section
3. Laryngoscopy
4. Intubation
5. Gastro Tube Insertion
In the above example, only Number 2, Cesarean Section, should probably be billed, the remaining above codes being procedures that should normally encompass the service of a Cesarean Section.
Another example of unbundling from a different area of health care rendition concerns pain management where a single office visit can fraudulently generate several different bills for one diagnostic work-up, as well as treatment of several different segments of the body. A separate trigger for pain management unbundling is described below because the unbundling practice is so frequently encountered in pain management.
The unbundling trigger of the present invention thus alerts the user of the software of the present invention as to any patient who has had more than one procedure performed on them in the same day or same event-day where treatment may have begun before midnight and ended after midnight in a single continuous treatment session. Obviously, there are some occasions when patients legitimately need to return to the operating room and those cases are accepted as fair billing practices.
Upcoding:
Another method that anesthesiologists use to inflate the price of the bill is called upcoding. This includes recording a fraudulent CPT Code (current procedure terminology that the surgeon uses to evaluate the procedure of the surgery performed), and by so doing, the provider (e.g., an anesthesiologist) can be compensated more than if he/she had recorded a legitimate CPT code on a payment claim for performing the case. The anesthesiologist must place the same CPT Code on the HCFA 1500 form as the surgeon, otherwise, it should be suspected as fraudulent upcoding. For example, if a surgeon designates as a Sigmoidoscopy as having been performed but the anesthesiologist records a CPT Code reflecting a Colonoscopy, which a similar but more extensive and more expensive procedure, the upcoding anesthesiologist will overbill the payer anywhere from two to three hundred Dollars. Such practices occur because the upcoding anesthesiologist cannot get caught by claim examiners who do not have the knowledge or computer resources to compare the surgeon-reported data with the anesthesiologist""s claims. This invention solves that claim-examining problem. In this case of the Upcoding trigger as applied to the medical specialty of, for example, anesthesiology, this invention solves the payer claim examining problem by specifically monitoring section 24D on the HCFA 1500 form of both the surgeon and the anesthesiologist, the present invention exposes upcoding.
Profiling Modifiers:
Besides unit value of a procedure, and time units, anesthesiologists also bill using modifiers. These include the following:
1. insertion of an arterial line
2. central venous pressure monitor
3. utilization of controlled hypotension
4. emergency
5. American Society of Anesthesiologists (ASA) evaluation upgrade
Furthermore, the anesthesiologist places a risk value to every patient undergoing anesthesia;
P1xe2x80x94normal patient
P2xe2x80x94patient with mild systemic disease
P3xe2x80x94patient with severe systemic disease
P4xe2x80x94patient that is in a constant threat to losing their life
P5xe2x80x94moribund patient not expected to survive 24 hours
If the anesthesiologist designates that the patient is evaluated at a P3-P5, he/she can charge an extra $100.00 to $300.00 dollars for performing the procedure.
The database that is installed into the software of the present invention gives the percentages of cases that are evaluated at P3-P5, as well as those that need the extra monitoring. By profiling the anesthesiologists, it is able to determine if any are billing abusing, placing unnecessary monitoring or placing higher risk values to patients so they collect larger fees.
Specifically, for example, if it is established over a long time, over a large geographic area or nationally, and over many JCAH (Joint Commission on Accreditation of Health Care Facilities) accredited institutions by statistically significant data that, for example, 3% of surgical patient""s are legitimately coded as risk category P3 but a particular anesthesiologist routinely codes all his/her patients as P3 it is beyond peradventure that said anesthesiologist is using the P3 designation fraudulently to get a larger paycheck from the insurance carriers to which payment claims are submitted.
$3,000 Threshold:
It is a standard in the industry for the anesthesiologist to be paid anywhere from one quarter to one third of what the surgeon is paid. It is highly unusual and aberrant for the anesthesiologist to be paid more than the surgeon.
The trigger here is to take every bill that exceeds a predetermined amount, preferably $3,000.00 at the time of this invention, analyze it to make sure it is not over billed and does not exceed the payments due the surgeon of the case.
In cases where the anesthesiologist""s bill does exceed the predetermined trigger amount, an additional calculation will be made comparing the anesthesiologist""s bill to that of the surgeon. When the bill ratio for anesthesiologist: surgeon exceeds about 1:3 a fraud flag for further scrutiny will be generated by the present invention.
Outpatient Units:
Outpatient settings are any procedure not performed in a J.C.A.H. (Joint Commission on Accreditation of Health Care Facilities) accredited facility (e.g., hospital). Rendering health care in a non-JCAH facility may be in a doctor""s office or in an outpatient surgical setting. This creates many opportunities for billing irregularities because the controls outside of a JCAH accredited facility are few. There is no accounting for time and because of the types of procedures performed in these non-JCAH settings, an anesthesiologist can render service to several patients in a short period of time but yet, bill hours for each case. Here again, the database of the present invention comes into play. When a bill is submitted a fraud flag is generated when the software determines that a procedure took place outside of a JCAH accredited facility, because within a JCAH facility there are fixed time limits are normally placed on reimbursements schedules.
Therefore, for example, if a Colonoscopy was billed six 15-minute time units for 1xc2xd hours and the database shows that 80% of Colonoscopies are performed within thirty minutes, then the payer need only to reimburse two 15-minute units for time rather than the billed six units.
Box 24B corresponds to location of surgical procedure field 11 shows an office procedure while field 24 shows that the procedure took place in an out patient surgical center. Because of the lack of controls there may be many more false claims filed from these non-JCAH facilities than JCAH accredited hospital based practice. Here too, the system applies a fair reimbursement data processing filter of a ratio of anesthesiologist to surgeon billing of about 1:3, or roughly at thirty percent of the surgical bill.
Pain Management Unbundling:
Pain management is frequently a problem area where fraudulent over-billing is encountered by payer insurance carriers. General medical billing Unbundling, as in Trigger 3, is so frequently encountered in the pain management specialty area that pain management unbundling requires its own separate fraud-flag trigger.
In pain management, for example, a sympathetic block of the lumbar region can include the following charges.
1. X-rays of the spine
2. Fluoroscopy of the spine
3. Local anesthesia
4. Insertion of needle
5. Injection of steroids
6. Sedation of the patient
7. Then multiple charges per each segment
These bills should be paid by the procedure itself and not be allowed to be unbundled. Codes that will be scrutinized to find evidence of pain management unbundling are the following:
20550xe2x80x94Trigger point injections
64520xe2x80x94Lumbar nerve block
62284xe2x80x94Myelogram
64440xe2x80x94Paravertebral nerve block
62289 Lumbar epidural
A fraud-flag will be generated by the present invention where pain management unbundling occurs as a pattern and practice of the billing of particular health care providers, when claims from such individuals are compared to other claims having been presented in the past by the same individuals.
No Fault/Disability:
The amount of medical fraud in regard to no fault automobile insurance as well as disability insurance is believed to be at epidemic levels. Apparently, there are neurologists, chiropractors and pain specialists whose practices thrive on producing large bills with complicated diagnoses, which allegedly help their patients inflate damages for pain in suffering lawsuits. Presently, the insurance industry does not do an effective job of profiling the physicians involved with the diagnosis and treatment for purposes of fraud detection and prevention. Each case itself may stand on its own merit but when a chiropractor is profiled and it is shown that he or she has given the same diagnosis and treatment schedule to hundreds of different patients then the proper investigational work-up will begin. The system of the present invention assists the insurance company with insight, interviews and opinions which their resources may have trouble accomplishing.
The no-fault/disability trigger is a data processing filter that examines multiple claims of a given provider for a pattern of repetitive diagnosing of the same injuries or patient conditions and flagging the provider as a possible fraud feasor and the repeatedly diagnosed injury or condition as one that lends itself to fraudulent abuse.